Voice programmable automatic identification and data capture devices and system

ABSTRACT

The proposed invention significantly lowers the burden of electronics data entry, as well as maintenance and configuration of an Automatic identification and data capture (AIDC) system, by making it programmable by voice and using artificial intelligence. Specifically, it proposes an AIDC sensor equipped storage container and AIDC system which can track items equipped with one or more AIDC tags, and any data can be associated, augmented, modified, removed or rewritten by using voice interaction by a user.

1 BACKGROUND

Automatic identification and data capture (AIDC) refers to the methodsof automatically identifying objects, collecting data about them, andentering that data directly into computer systems (i.e. without humaninvolvement). AIDC technologies include barcodes, RFID, bokodes, OCR,magnetic stripes, smart cards and biometrics (like iris and facialrecognition system). AIDC system typically consists of AIDC tags andAIDC sensor connected to processing units.

AIDC systems have been used in commercial systems extensively forinventory management and logistic tracking. However, it has not got muchof traction in consumer market in home settings. One of the main hurdlesfor adopting such a system for such market is the cost of programmingand maintaining AIDC system using data entry for various items. In orderfor AIDC systems to be useful, generally each AIDC tag must beassociated with some useful data at least once (such as what that AIDCtag is attached to). Such data is typically entered using data entry inan electronic form. Moreover, over time, such associated data isaugmented, modified, removed or rewritten, which also require additionaldata entry work. Even when data is available in an electronic form,association/modification of that data to AIDC tag with correctconfiguration can be complicated. Such tasks, as well as electronic dataentry, are typically time consuming and inconvenient which requiresignificant time, effort and technical know-how by the user. Without theeconomy of scale, cost and inconvenience of such tasks frequentlyoutweigh the advantages of using AIDC system. For the same reasons, AIDCsystems have not been successful in small business or developingcountries, as the overhead and cost of implementing such systems eclipsethe benefits.

2 PROPOSED INVENTION

The proposed invention significantly lowers the burden of electronicsdata entry, as well as maintenance and configuration of the system, bymaking it programmable by voice and using artificial intelligence.Specifically, it proposes an AIDC sensor equipped storage container andAIDC system which can track items equipped with one or more AIDC tags,and any data can be associated, augmented, modified, removed orrewritten by using voice interaction by a user.

2.1 DESCRIPTION

Attached FIG. 1 presents the proposed voice programmable AIDC system.

-   -   101 is a storage container where physical items are stored and        retrieved by the user. Such storage item may be of any size        (small box, large warehouse). It may be stationary or mobile        (e.g. enclosed container in a truck.) It may provide additional        services apart from storage, e.g. refrigeration.    -   102 is a division of the container that divides containers in        separate sections (e.g. shelf in a cabinet). Such division may        be physical or logical.    -   103 (plane with the gray diagonal pattern in FIG. 1.) is the        plane of opening/accessing the container. Items can only move in        and out of the container by crossing the plane. Container may        have more than one opening/access planes. For simplicity and        brevity, the document describes operations with only one        opening. That is, the presented technique can be extended to        multiple openings by implementing a plane crossing detection        mechanism for all planes.    -   104 represents any physical storage item that a user wishes to        store and retrieve from the container.    -   105 is an AIDC tag. Such tag may be integrated part of the        storage item or it may be removable and attachable to the        storage item.    -   106 is an AIDC detector which can (a) detect AIDC tag crossing        the access plane and/or (b) presence/absence of AIDC tag in        container. Such detection may require a special user action        (such as bringing AIDC tag near to sensor) or it may happen        without any special action from the user (e.g. just passing AIDC        tag from the opening.) One or more AIDC sensor may be used for        one container. Such AIDC sensors may be mounted on/integrated in        the container or it may be separate and kept nearby its opening.    -   107, 108, 109, 110 are optional auxiliary sensors which is able        to detect, without the use of AIDC tag, (a) a storage item        crossing the access plain and/or (b) addition/subtraction of        storage item in the container (e.g. optical obstacle detector,        camera, etc.). Moreover, such sensors may provide additional        information about items, e.g., weight sensor can provide storage        item weight. Moreover, auxiliary sensor may be able to provide        more granular information about the location of the storage item        within the container. (E.g. which shelf the item is placed.) One        or more auxiliary sensors may be used for the same container.    -   111 is a microphone which is used by the user to provide        information to the AIDC system. 112 is a speaker that AIDC        system utilizes to inform and inquire the user.    -   111 and 112 may be integrated in (or mounted on) container or it        may be separate (e.g. in a user's mobile phone)    -   113 is a processor unit that is connected (either wired or        wirelessly) to AIDC sensor (106), auxiliary Sensors (107-110),        microphone (111) and speaker (112). Processor unit is able to        read and command connected components. 113 may be integrated in        (or mounted on) container or it may be separate (e.g. in a        user's mobile phone)

Processor unit 113 is connected vial link 114 to a network connectedserver (e.g. cloud server) 115. This server may contain a database tokeep track of the items (104) in one or more containers (101).

Moreover, server (115) may store and execute Artificial Intelligence(AI) module (118). Such AI module may possess capabilities of multiplerelevant domains, including but not limited to, audio processing, speechrecognition, natural language processing, machine learning, expertsystems and user behavior prediction for inventory management.Optionally, all or a part of the AI module (118) may be stored andexecuted on processing unit (113) or end-user computing devices (117).

Server (115) is connected to end-user computing devices 117 (e.g. Mobilephone or PC) via link 116, which enable 117 to view and modify data orconfiguration of the proposed AIDC system. End-user computing device(117) may be mounted on the container (101) itself, such as touch screendisplay.

Each storage item (104) may be associated with “title information” (e.g.Name, identification number, category, or ingredient.) which helps usersto recognize the item, type of the item or content of the item. Apartfrom the title information, and item may be associated with metadatawhich provides additional information (e.g. expiry date, quantity,intended use, the target user information, notes etc.).Content/components of such title information and metadata arecustomizable by the user.

2.2 OPERATION

Any speech input from a user, provided via microphone (111), istransmitted to the processing unit (113) for processing and recognition.Processing unit (113) may further send the speech (or processedinformation about the speech, or both) to the networked server forinterpreting and understanding the speech input. After recognizing thespeech, AI module determines and executes the appropriate action (suchas updating inventory in data base). Additionally, AI module may informthe user about the action taken or ask for more information via speaker(113).

When a user adds or removes a storage item (104) with AICD tag (105)through opening (103) inside/outside of the container (101), such eventis detected by AIDC detector (106), and conveyed through processing unit(113) and link (114) to networked server (115).

AIDC system's operates on the contextual information exchange i.e. oncethe AIDC tag (105) is detected going inside or outside of the storagecontainer (101), current context is set to detected AIDC tag (105) andinformation passed to/from the user using speech/audio it regarding thestorage item (104) is associated with the detected AIDC tag (105),unless explicitly stated otherwise. This kind of contextual processingis a one of the key part to increase user-friendliness of the proposedinvention.

Here, after any addition/removal of AIDC tag (105) from container (101),if any title information is available, AIDC system may announces thetitle information to the user via speaker (112). In response, the usermay ask for adding or modifying the title information and any associatedmetadata data by speaking into microphone (111).

If no AIDC tag (105) is attached to the storage item (104), auxiliarysensors (107-110) may still be able to detect the event ofaddition/removal of the storage item (104) in the container (101). Insuch cases, the user is prompted via speaker (112) to attach the AIDCtag and repeat the addition/removal action. If AIDC tag (105) isattached to the storage item (104), any information obtained by usingaxillary sensors (107-110) (e.g. weight or the item from weight sensors,or brand of the item using camera) is automatically associated with thedetected AIDC tag (105).

For each entry and exit of a storage item, the processing unit (113)receives data about the entry/exit even, detected AIDC tagidentification, event timing, title information, metadata andinformation provided by auxiliary sensors. This data is passed tonetworked server (115) and it is processed, analyzed and stored by AImodule (118) in the network server (115). Alternatively, some or all ofsuch processing and analysis may be performed in the processing unit(113).

Processing of this raw data by AI combined with information fromexternal sources (such as internet) may generate, a number of usefulderived information and metadata regarding the item (e.g., creation ofreminder for removal of an item). Moreover, history of the raw data, thederived information and calculated statistics may be maintained in theserver (115), which may be used for AI for machine learning. Data storedon server made available to the en-user devices using an Application(e.g. App in mobile phone).

2.3 TECHNIQUES TO IMPROVE USABILITY AND OPERATIONS WITH VOICE INPUTS

Current speech recognition system has limited accuracy, particularlywhen it comes to special names which are not part of languagedictionary. In case of inventory management, such names frequently carrysignificant and crucial information. E.g. Name of medicine, ethnic fooditems name etc. The challenge is compounded when such names arepronounced by using different users with widely varying accents. Theproposed invention utilizes a number of techniques to alleviate theproblem and make the system more user-friendly.

-   -   (1) Storing, differentiating and utilizing original speech        segment: Irrespective of how well the user speech segment is        recognized, the original speech segment may also be stored with        associated AIDC tag, and replayed to the user when possible (and        appropriate). For example, name of an item will be read back to        the user in user's voice. The item is identified by        characteristics of sound of its title information (a.k.a. sound        signature) rather than the recognized name. This way, even if        the name is not recognized properly, many of the inventory        management functions can work, as long as ‘sound signature’ of        the title information is distinguishable compared to the sound        signature of the other items in the storage container. This is        particularly important when system encounters names missing from        standard vocabulary e.g. ethnic food name “aalo-gobhi”.    -   (2) Interactive mode with immediate feedback: AI module (118)        may ask for clarification to the user if AI is not able to        understand (or have ambiguity regarding) a part or the whole of        the speech input provide by the user. Moreover, AI module may        selectively convey back recognized segment of the speech (or        information derived from it) for confirmation. Such information        is also immediately made available to end-user computing devices        (117) for visual confirmation. The user is able to correct any        misrecognized/incorrect information through new voice commands        or interacting with any end-user computing devices. Contextual        nature of the interaction makes these actions more        user-palatable.    -   (3) Narrow domain and adaptive AI: Unlike general speech        processing, (e.g. dictation), interaction about the storage        management and related activities requires much smaller set of        options and vocabulary. Moreover, depending upon the application        of the storage, this vocabulary can be narrowed even further.        For example, working with kitchen refrigeration, drug storage        and filing cabinet is likely to have different distinct        vocabularies and/or sentence structure; and AI module may avail        the knowledge about the application to improve speech        recognition. Furthermore AI may utilize the history of user        actions/correction for deep learning and adaptive user action        prediction to improve speech recognition and other functionality        by mapping it to application-specific and user-specific actions.    -   (4) Limited language patterns and keywords/key phrases: To        improve operations for certain applications, the proposed AIDC        system may restrict acceptable user input to certain language        patterns (e.g. all user inputs must be imperative sentences.)        Moreover, system instruction may provide the user a list of        certain limited keywords/or key phrases for performing specific        actions or conveying specific information (e.g. “Reminders after        3 days”, “Expires on”).    -   (5) Only relevant and unobtrusive feedback though adaptive AI:        One of the most important usability aspect of the proposed AIDC        system is that the system provides only relevant and timely        feedback and information, through adaptive learning in AI. Some        examples are: (a) if a user asks same type of question about        metadata repeatedly for a particular type of item, next time        when such item entry/exit is detected system provides that        information without the user asking for it (2) When a user cuts        off the additional information being provided by the system,        particularly with some key phrases like “yeah, that's enough”,        next time information will be curtailed for the item. (The        system continues to listen to the user even while providing the        information through the speaker.) (c) AI attempts to detect        distinct mode of operation and predict operation/behavior based        on all information available. For instance, when significant        number of items is rapidly exiting/entering the system, the user        may be performing restocking in bulk and the user may not be        interested in hearing metadata or even title information for all        items. AI system may learn from one user or by combining        multiple user data from cloud services.    -   (6) Interactive and configurable through end-user computing        devices: all system settings and data may be made available        through applications on end-user computing devices with user        familiar interfaces, instead of crammed, inflexible and        unappealing user-interface mounted generally on storage        container.    -   (7) Use of metadata to provide other Internet connected        services: Since a user can attach any metadata easily with any        tag, it creates a rich platform for providing a number of other        Internet connected services, based on metadata, such as emails        notification, calendar event, produce shopping list, ordering        low stock item etc.    -   (8) Many products come with inbuilt AIDC tag, e.g. UPC barcode.        With barcode reader, the proposed system can look up the UPC        barcode and fetch the related data, if available, and announce        it to the user. The user can augment or modify the data. More        importantly, in case where the barcode is unrecognized, the user        can instruct the system what it is. The system learns and        remembers the information associated with the barcode. Next time        when the same barcode is detected, the system will recognize it        and announce the associated information.

3 SPECIFIC APPLICATION—CONTENT-AWARE SMART KITCHEN REFRIGERATOR

One of the very useful application for the system is for making smartkitchen refrigerator. Current issue with the so called “smart”refrigerator (a.k.a. fridge) in the market is that it does not have veryuser-friendly, general and robust system to make it content aware. Thetypical current techniques used for detecting contents are:

-   -   (1) Use of cameras to read the labels for items: this method is        not robust or user friendly because (a) it difficult to get        clear shot of labels in congested fridge. (b) The user hands may        be blocking the view. (c) You may need many cameras from        different angle to overcome (b), making system very costly (d)        Optical character recognition technology is not robust to        recognize the content, particularly, when image is captured from        video frame of a moving object. (e) Cannot detect content in        user utensils (e.g. left overs or cooked item) which are not        labeled. Not only adding written label for each of utensil is        cumbersome, the same utensils are reused with different content        which requires removing previous labelling and relabeling        them. (f) If the user has to add any metadata, they have to        manually type the information in some input devices.    -   (2) Use barcode reader: this method is inconvenient and        limited. (a) There is no universal barcode system with        associated data base. Each store or manufacturer may have its        own barcode system. Hence, even after reading the barcode on        product, that bar code may not be correctly recognized. (b)        Range of barcode reader is limited, and barcode of product must        be brought nearer to the reader, facing the reader. Performing        this special action every time putting or taking away each item        from fridge is cumbersome. Limitation of (1)(e-f) also applies.

The proposed solution is to adopt system proposed in Section 2 asfollowing:

-   -   1. Fridge as storage container (101)    -   2. Shelf in the fridge as division of the container(102)    -   3. Door of the fridge as plain of opening/access (103)    -   4. Any storage item (box/bottle/utensil) for fridge is a storage        item (104)    -   5. A passive/active RFID tag as AIDC tag (105). Tags should be        easily attachable and removable for any container, like reusable        stickers    -   6. RFID detector as AIDC detector (106) which can either (a)        detect an RFID tag going in or out of the fridge door or (b) it        can detect presence or absence of an RFID tag in the fridge.        This RFID detector should be ideally capable of performing        detection of RFID tag attached with storage items with natural        user actions of putting things in an out of the fridge, (without        requiring special user action or consideration like hand and tag        placement.)    -   7. Weight sensors under each shelf are auxiliary sensors        (107,110). Not only such weight sensor can identify entry and        exit event by monitoring weight change, it can provide weight        information about the identified items.    -   8. Microphone (111) and speaker (112) are embedded in (or        attached to) the fridge door opening.    -   9. Processing unit is an embedded processor (113) that is        connected to internet and sensors. It is connected to Server        (115) running AI module (118) through internet.    -   10. Mobile Phone, tablet or PC are end-user devices (117), which        access server data through special apps.

Detection of RFID tag going in or out of the fridge is indicated bydistinct short sound on speaker like “Beep” or “Ding”. Title informationof the storage item will be provided by the user which will be typicallythe name of the content in the storage item.

3.1 Operation

When a user opens the door of such fridge and puts in (or takes away)any item with RFID tag in the fridge, the fridge detects it with a“Ding” sound. If no item name is associated with tag, fridge asks theuser (through voice on speaker), to identify the item. The user mayprovide the name of the item along with any metadata by speaking throughthe microphone.

If the tag has associated item name from its last use, fridge announcethe name (along with any information deems pertinent by AI module andsystem configuration). The user may override the name and/oradd/override metadata data by speaking new name/metadata. Example ofsuch metadata and related system action is provided in a sample scenarioat described in section 3.1.1.

If the item has no associated tag, weight sensors will still detectentry/exit event due to detected weight change, and prompt the user toadd a tag to the item.

Announcing the name and some metadata may be performed by replaying therecorded user voice to minimize the effect of limitations of speechrecognition. In cases where announcement is not configured to beperformed using recorded the user voice, the user can ask to replay itin original recorded voice and issue commands for further actions.

3.1.1 Sample Usage Scenario:

[Scene] User Julia came home after light grocery shopping and wishes toadd some of shopped item in the fridge while also reviewing the existingcontent of the fridge. The user interacts with fridge using microphoneand speakers. Any update in content detected by the fridge is conveyedto connected cloud server. For simplicity, the entire AIDC system willbe referred as fridge, in this scenario, because that is what the userperceives.

Julia opens the fridge door.

[Fridge]: “Welcome back.” Here, it is a greeting message.

[Julia:]: “Hello, Alice. Julia here.” Here, Alice is the user-give nameof this fridge. Julia indemnifies herself as the user. This puts smartfridge in the context of the user Julia.

Julia takes a grab a bag of tomatoes from shopping bag, add an RFIDstickers, and puts bag in the fridge. As tomatoes bag is crossing thedoor, system detects the RFID tag with “Ding” sound and Julia says

[Julia:] “Tomatoes.” Fridge registers that tag is associated withtomatoes and its weight (using difference in weight registered by weightsensors.)

Julia takes a milk carton from shopping bag, adds an RFID sticker, andputs the item in the fridge. As milk is crossing the door, systemdetects the RFID tag with “Ding” sound and Julia says

[Julia:] “Milk. Expires in two weeks.” Here, meta data is being added innatural language. Fridge registers item name and the weight with the tagand also adds expiry date for the item. This expiry date can be used formultiple purposes, like creating reminder or viewing items by expirydate in mobile app etc. If Julia did not add expiry date, fridge willstill estimate it based on cloud analytics.

Julia added an item with a tag but forgot to say the name.

[Fridge:]: “That's new, what is it ?” This is a feedback/question innatural language by the system.

[Julia:] “It's Peach”. The fridge is still in the context of the lastdetected tag. Hence, its name and weight is added to the tag.

Julia takes out a container to make space. System detects out goingobject with “Ding” and based on the last used name, announces

[Fridge:] “Soup.”

Julia takes out the container. System recognizes it with “Ding” andannounces

[Fridge:] “Blueberries.”

[Julia:] “Discard this”.

[Fridge:] “OK. Discarded” Fridge resets any information associated withthat tag. Tag can now be reused for another item. Moreover, it registersthe waste item with its weight. This is used for maintaining wastestatistics and history. Julia adds another bag with tag.

[Julia:] “Red papers. Add note: this is for Friday dinner.” Systemregisters the name and its weight for the tag. Moreover, metadata isused for meal planning app. Julia takes out some soup that was outside,pour some of it in another bowl and puts back soup bowl. Systemrecognizes with “Ding” and announces “Soup.” Weight change will be notedto know consumption of soup from the container.

Julia puts a box of pasta but forgot to put a tag.

[Fridge:] “No tag? Can you add one?”

Julia takes it out, adds tag and puts it back.

[Julia:] “Pasta. Remind me to finish by tomorrow evening.”

[Fridge:] “OK.” Name and weight is added for the tag and reminder iscreated for tomorrow evening.

Julia puts a new container with tag and Fridge recognizes it as“Oatmeal”.

[Julia:] “No, it's Lasagna now.”

[Fridge:] “OK, updated.” Tag information is overridden here.

Julia adds a box with a tag.

[Julia:] “Cake. Add note to share with neighbors.” Note in originalvoice will be associated with tag along with name and weight.

Julia is planning to close the fridge.

[Julia:] “Bye Alice.”

[Fridge:] “Wait, you have expired humus in the top shelf and stoleraspberry on the bottom shelf.” Here, AI module decides to volunteersome pertinent information.

Julia takes out humus. Fridge recognizes it with “Ding” and announces“Humus.”

[Julia:] “Discard this.”

[Fridge:] “OK, discarded”

Julia takes out raspberries. Fridge recognizes it with “Ding” andannounces “Raspberries”.

Julia examines raspberries and puts it back in the fridge. Fridgerecognizes it with “Ding” and announces “Raspberries”.

[Julia:] “These are still good for two days. Remind me to take to officetomorrow.”

[Fridge:] “OK, updated.” Fridge updates expiry date for the tag andcreates a reminder service. Here information associated with the tag isreprogrammed on-the-fly using voice command.

4 SPECIFIC APPLICATIONS—STORAGE CABINENTS 4.1 Medicine Cabinets

Here, medicine cabinet is the storage container, medical supplies(bottles, strips etc.) are storage items. Items can be attached with anactive/passive tags RFID tags. RFID detector detects movement of taggoing in and out of the cabinet. Microphone and speaker are embedded in(or attached to) the cabinet.

Similar to the operation described in section 3.1, user will pronouncethe name of the item and other associated useful information (expiry,quantity, purpose, dosage) when putting in the item first time. Fromthen on, system will announce existing information while taking out orputting the item with the same tag and the user can modify theinformation through voice input if needed.

All the information stored in the system is accessible via user deviceslike mobile phones or tablets via internet connected server.

For cost saving purpose, RFID tag and sensor can be replaced by barcodestickers and sensors. Here users need to perform the additional actionto bring the barcode near to the sensor while taking out or puttingitems in the cabinet. The barcode may be the build-in UPC code on themedical product.

Both small hospitals and home medicine cabinets can benefit from thisinvention. Every year, millions of dollars of medicine is expired andwasted all around the world in home cabinets or small hospitals due tolack of easy-to-use cost effective inventory system. With internetconnected medical cabinets, aggressive medicine donation programs can besetup to reduce this waste. Moreover, data related to consumer medicineusage and patterns are very valuable for consumer research and medicalresearch alike.

4.2 Document Filing Cabinets

Despite progress in electronic documentation, we still deal with verylarge number of important printed documents during our life. Thesituation is even worse in developing countries where laws require youto maintain printed documents. Keeping track of all available personaldocuments in house or commercial documents in a small company is acumbersome and error prone task.

With the proposed system with barcode as AIDC tag and barcode sensor asAIDC sensors, user can simply put barcode label on the document, scanthe code in barcode reader and announce the relevant information. Thisinformation can include additional information about location such as“Home Insurance Records. It is placed in to top drawer in a green filealong with property tax records.” This way, one scanner can be used formultiple cabinets and it can be completely mobile. In fact, mobile phoneitself can act as multiple components in the proposed system (mic,speaker, processing unit and scanner) and system can be implementedwithout any physical modification to the filing cabinet.

5 SPECIFIC APPLICATION: WAREHOUSING

There is no restriction on the size of the storage container. Thecontainer can be an entire warehouse or a shop, where door or checkoutpoint will become access planes. For instance, a small shop in adeveloping country can print its own barcode labels and quicklyassociate item name and price with the barcode without any manual dataentry on computer. This will allows small shop keepers to avail the samebenefits of sophisticated inventory management and analysis that iscurrently only available to big stores who can afford high volumesystems with associated data entry costs.

6 SPECIFIC APPLICATION: WINE CONNOISSEUR OR SHOP ASSISTANT

A wine shop can install the proposed system to improve its userexperience. RFID AIDC tags will be attached to wine bottles and RFIDAIDC sensors will installed near the entrance of the wine cabinet. Here,not only wine shop can an get automated inventory management system andcan also get a virtual wine connoisseur or assistant. When a customerpicks up a bottle from a cabinet shelf, system will detect the movementand provide information about the vine that customer picked up, such aswine's name, history and pedigree, taste attributes and compatiblefood/beverage combinations via speaker. Such information may bepre-recoded by wine shop owner, wine producer or any third party.Alternatively such information may be retrieved from internet/databasein the text form and conveyed to user using voice synthesizer.

Similarly, the system can act as a knowledgeable assistant in any shopor settings where knowledge about individual item is frequently desiredby users. For example, antique shops or handicraft shops. Frequentlysuch information is a key ingredient for successful sale to shoppers andit takes long time to train and retain knowledgeable employees.Moreover, an employee can handle only one customer at a time while theproposed system can act independently and automatically for eachcabinet, making it much more scalable.

7 EMBODIMENT OF THE COMPUTING SYSTEM AND SOFTWARE

Embodiments of the invention may be implemented on a computing system.Any combination of mobile, desktop, server, router, switch, embeddeddevice, or other types of hardware may be used. For example, a computingsystem may include one or more computer processors, non-persistentstorage (e.g., volatile memory, such as random access memory (RAM),cache memory), persistent storage (e.g., a hard disk, an optical drivesuch as a compact disk (CD) drive or digital versatile disk (DVD) drive,a flash memory, etc.), a communication interface (e.g., Bluetoothinterface, infrared interface, network interface, optical interface,etc.), and numerous other elements and functionalities.

The computer processor(s) may be an integrated circuit for processinginstructions. For example, the computer processor(s) may be one or morecores or micro-cores of a processor. The computing system may alsoinclude one or more input devices, such as a touchscreen, keyboard,mouse, microphone, touchpad, electronic pen, or any other type of inputdevice.

The communication interface may include an integrated circuit forconnecting the computing system to a network (e.g., a local area network(LAN), a wide area network (WAN) such as the Internet, mobile network,or any other type of network) and/or to another device, such as anothercomputing device.

Software instructions in the form of computer readable program code toperform embodiments of the invention may be stored, in whole or in part,temporarily or permanently, on a non-transitory computer readable mediumsuch as a CD, DVD, storage device, a diskette, a tape, flash memory,physical memory, or any other computer readable storage medium.Specifically, the software instructions may correspond to computerreadable program code that, when executed by a processor(s), isconfigured to perform one or more embodiments of the invention.

1. A system, comprising: a storage container for storing a plurality ofphysical storage items, wherein an identifier tag is integrated orattached with each of the plurality of physical storage items, thestorage container comprising: at least one access plane which is passedthrough to add or remove each of the plurality of physical storage itemsin the storage container, a sensor configured to detect an event ofadding or removing a storage item to the storage container with anidentifier tag either by: (a) detecting the identifier tag crossing theaccess plane, or (b) monitoring a presence or an absence of theidentifier tag within the storage container; a microphone and speakerfor communicating with the system, wherein the microphone is configuredto receive natural language audio input from a user and the speaker isconfigured to provide audio feedback to the user; and a processing unit,operatively connected to the storage container, sensors the microphoneand the speaker, and configured to: track each of the plurality ofphysical storage items in the storage container, perform audioprocessing on the natural language audio input to determine titleinformation and other metadata for each of the plurality of storageitems being added to or removed from the storage container, wherein thenatural language audio input is selected from a narrow domain of likelywords associated with an application of the storage container, associatethe title information and other metadata to the identifier tagassociated with each of the plurality of physical storage items, store,in associated memory, the identifier tag mapped to the associatedstorage item, and change the title information or other metadata for atleast one of the plurality of storage items based on natural languageaudio input provided a next time that the at least one storage item isbeing added to or removed from the storage container.
 2. The system ofclaim 1, wherein the identifier tag is an automatic identification anddata capture (AIDC) tag.
 3. The system of claim 1, further comprising: aplurality of auxiliary sensors operatively connected to the processingunit for detecting one or more of the following: a weight of each of theplurality of storage items, a location of each of the plurality ofstorage items within the storage container, and passing of each of theplurality of storage items through the access plane.
 4. The system ofclaim 1, wherein the processing unit is operatively connected to a cloudserver comprising a database for storing and tracking each of theplurality of storage items, associated title information, and metadatafor each item.
 5. The system of claim 1, wherein the title informationcomprises at least one selected from a group consisting of: a name ofthe at least one physical storage item and a category of the at leastone physical storage item, and a content of the at least one physicalstorage item, when the at least one physical storage item was added orremoved from the storage container.
 6. The system of claim 5, wherein aportion of the title information and/or a portion of the other metadatais not recognized by the system.
 7. The system of claim 1, wherein thenatural language audio input comprises a voice input forming a speechsegment, and wherein the processing unit is further configured to:store, in the associated memory and as a portion of the titleinformation or other metadata, the speech segment; and replay the speechsegment as the audio feedback to the user.
 8. The system of claim 7,wherein the speech segment is not recognized by the system, and isstored as part of the title information in the identifier tag in anoriginal, unrecognizable form.
 9. The system of claim 1, wherein theprocessing unit is further configured to: operate in an interactivemode, wherein the system prompts the user for additional informationwhen the natural language audio input is not recognized by the system.10. The system of claim 1, wherein the other metadata comprises at leastone selected from a group consisting of: a timestamp for when the atleast one physical storage item is added or removed from the storagecontainer, an email notification related to the least one physicalstorage item, an expiry of the at least one physical storage item, anannotation associated with the at least one physical storage item, acalendar event related to the least one physical storage item.
 11. Thesystem of claim 1, wherein the processing unit is operatively connectedto a server in the cloud computing environment, wherein the servercomprises an artificial intelligence module that is configured to learnfrom the user input and historical user behavior, to estimate the othermetadata and improve natural language audio input recognition.
 12. Anon-transitory computer readable medium comprising instructions, thatwhen executed by a processing unit, are configured to perform a method,the method comprising: tracking each of a plurality of physical storageitems in a storage container, wherein an identifier tag is integratedwith each of the plurality of physical storage items, and wherein thestorage container comprises: at least one access plane, which is passedthrough to add or remove each of the plurality of physical storage itemsin the storage container, a sensor configured to detect an event ofadding or removing a storage item to the storage container with theidentifier tag either by: (a) detecting the identifier tag crossing theaccess plane, or (b) monitoring a presence or an absence of theidentifier tag within the container; receiving a natural language audioinput from a user; performing audio processing on the natural languageaudio input to determine title information and other metadata for eachof the plurality of physical storage items being added to or removedfrom the storage container, wherein the natural language audio input isselected from a narrow domain of likely words associated with anapplication of the storage container; associating the title informationand other metadata to the identifier tag associated with each of theplurality of physical storage items, storing, in associated memory, theidentifier tag mapped to the associated storage item, and changing thetitle information or other metadata for at least one of the plurality ofstorage items based on natural language audio input provided a next timethat the at least one storage item is being added to or removed from thestorage container.
 13. The non-transitory computer readable medium ofclaim 12, wherein the natural language audio input comprises a voiceinput forming a speech segment, and wherein the method furthercomprises: storing, in the associated memory and as a portion of thetitle information, the speech segment; and replaying the speech segmentas the audio feedback to the user.
 14. The non-transitory computerreadable medium of claim 13, wherein the speech segment is notrecognized by the system, and is stored as part of the title informationin the identifier tag in an original, unrecognizable form.
 15. Thenon-transitory computer readable medium of claim 12, wherein the methodfurther comprises: prompting, in an interactive mode, the user foradditional information when the natural language audio input is notrecognized by the system.
 16. The non-transitory computer readablemedium of claim 12, wherein the title information comprises at least oneselected from a group consisting of: a name of the at least one physicalstorage item and a timestamp indicating when the at least one physicalstorage item was added or removed from the storage container.
 17. Thenon-transitory computer readable medium of claim 16, wherein the titleinformation is not recognized by the system.
 18. The non-transitorycomputer readable medium of claim 12, wherein the natural language audioinput comprises a voice input forming a speech segment, and wherein themethod further comprises: storing, in the associated memory and as aportion of the title information, the speech segment; and replaying thespeech segment as the audio feedback to the user.
 19. The non-transitorycomputer readable medium of claim 18, wherein the speech segment is notrecognized by the system, and is stored as part of the title informationin the identifier tag in an original, unrecognizable form.
 20. Thenon-transitory computer readable medium of claim 12, wherein the methodfurther comprises: combining information from the sensor withinformation from a plurality of auxiliary sensors for detecting one ormore of the following: a weight of each of the plurality of storageitems, a location of each of the plurality of storage items within thestorage container, and passing of each of the plurality of storage itemsthrough the access plane, to obtain a complete information for each ofthe plurality of storage items.